Researchers propose a new paradigm called "provable probabilistic safety" to address the challenge of ensuring safety for scalable embodied AI systems in complex environments. This approach integrates statistical methods with provable guarantees to enable practical and safe deployment at scale, particularly in critical domains like autonomous vehicles and medical devices. By defining a clear probabilistic safety boundary, this framework aims to facilitate broader adoption while managing inherent risks effectively.
Read the full article at arXiv cs.AI (Artificial Intelligence)
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Ali NematiWritten by Ali
